Hitachi
AI Data Architect
Dallas, Texas, United States · Hybrid · Full-time · Posted Oct 27, 2026
- Experience
- 12+ years in data architecture, data engineering, or analytics architecture.
About the job
Designs semantic, knowledge, and governance layers so AI agents can use trusted, structured, and governed data.
What you'll do
- Design metrics layers, ontology frameworks, search indexes, and business glossaries.
- Assess data readiness and translate business rules from subject matter experts into reusable, governed models.
- Define entitlement frameworks, data lineage standards, and agent identity requirements.
What they ask for
- Expertise with lakehouse and cloud-based data platforms and strong knowledge of semantic layers, metrics, dimensional modeling, and domain-driven data modeling.
- Hands-on experience with ontologies and knowledge graphs, plus vector databases, semantic search, embeddings, and RAG architectures.
- Deep understanding of data governance and proficiency in data quality, reconciliation, and readiness assessments.
- Proven enterprise-scale delivery of a semantic layer, knowledge graph, or governed data product; experience leading SME workshops and presenting recommendations to senior stakeholders.
Nice to have
- Domain experience in automotive, manufacturing, or supply chain.
- Exposure to GenAI grounding, text-to-SQL, natural language analytics, or relevant professional certifications.
Tools
Databricks, Delta Lake, Unity Catalog, PySpark, RDF/OWL, Neo4j, Kafka, Amazon MSK
AI focus
Designs data foundations and governance that enable AI agents; the role also involves vector search, embeddings, RAG architectures, and may involve GenAI grounding techniques.
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